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High Resolution Detection and Analysis of CpG Dinucleotides Methylation Using MBD-Seq Technology

Author

Listed:
  • Xun Lan
  • Christopher Adams
  • Mark Landers
  • Miroslav Dudas
  • Daniel Krissinger
  • George Marnellos
  • Russell Bonneville
  • Maoxiong Xu
  • Junbai Wang
  • Tim H-M Huang
  • Gavin Meredith
  • Victor X Jin

Abstract

Methyl-CpG binding domain protein sequencing (MBD-seq) is widely used to survey DNA methylation patterns. However, the optimal experimental parameters for MBD-seq remain unclear and the data analysis remains challenging. In this study, we generated high depth MBD-seq data in MCF-7 cell and developed a bi-asymmetric-Laplace model (BALM) to perform data analysis. We found that optimal efficiency of MBD-seq experiments was achieved by sequencing ∼100 million unique mapped tags from a combination of 500 mM and 1000 mM salt concentration elution in MCF-7 cells. Clonal bisulfite sequencing results showed that the methylation status of each CpG dinucleotides in the tested regions was accurately detected with high resolution using the proposed model. These results demonstrated the combination of MBD-seq and BALM could serve as a useful tool to investigate DNA methylome due to its low cost, high specificity, efficiency and resolution.

Suggested Citation

  • Xun Lan & Christopher Adams & Mark Landers & Miroslav Dudas & Daniel Krissinger & George Marnellos & Russell Bonneville & Maoxiong Xu & Junbai Wang & Tim H-M Huang & Gavin Meredith & Victor X Jin, 2011. "High Resolution Detection and Analysis of CpG Dinucleotides Methylation Using MBD-Seq Technology," PLOS ONE, Public Library of Science, vol. 6(7), pages 1-11, July.
    • Handle: RePEc:plo:pone00:0022226
    DOI: 10.1371/journal.pone.0022226
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    References listed on IDEAS

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    1. Vishwanath R. Iyer & Christine E. Horak & Charles S. Scafe & David Botstein & Michael Snyder & Patrick O. Brown, 2001. "Genomic binding sites of the yeast cell-cycle transcription factors SBF and MBF," Nature, Nature, vol. 409(6819), pages 533-538, January.
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    Cited by:

    1. Zhaohui Qin & Ben Li & Karen N. Conneely & Hao Wu & Ming Hu & Deepak Ayyala & Yongseok Park & Victor X. Jin & Fangyuan Zhang & Han Zhang & Li Li & Shili Lin, 2016. "Statistical Challenges in Analyzing Methylation and Long-Range Chromosomal Interaction Data," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 8(2), pages 284-309, October.

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